Software for segmenting and quantifying calcium signals using multi-scale generative adversarial networks

STAR Protoc. 2022 Dec 16;3(4):101852. doi: 10.1016/j.xpro.2022.101852. Epub 2022 Nov 15.

Abstract

Cellular calcium fluorescence imaging utilized to study cellular behaviors typically results in large datasets and a profound need for standardized and accurate analysis methods. Here, we describe open-source software (4SM) to overcome these limitations using an automated machine learning pipeline for subcellular calcium signal segmentation of spatiotemporal maps. The primary use of 4SM is to analyze spatiotemporal maps of calcium activities within cells or across multiple cells. For complete details on the use and execution of this protocol, please refer to Kamran et al. (2022).1.

Keywords: Cell Biology; Computer sciences; Microscopy.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Calcium*
  • Image Processing, Computer-Assisted / methods
  • Machine Learning
  • Neural Networks, Computer*
  • Software

Substances

  • Calcium